We’re seeking a skilled MLOps Engineer for one of our clients.

Requirements:

• 3+ years of experience in MLOps, ML engineering, or DevOps roles supporting ML systems
• Proficiency in Python and familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn
• Hands-on experience with orchestration tools (e.g., Kubeflow, MLflow, Airflow)
• Experience with cloud computing platforms (AWS, GCP, or Azure)
• Strong understanding of CI/CD concepts and version control systems like Git
• Familiarity with containerization and orchestration tools (Docker, Kubernetes)
• Experience with model monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
• Solid understanding of the ML lifecycle, from experimentation to production

Preferred Qualifications:

• Experience with infrastructure-as-code (Terraform, CloudFormation)
• Background in software engineering or data engineering
• Knowledge of responsible AI practices and model interpretability tools
• Certifications in cloud platforms or MLOps tools (a plus)